At present, with the flourishing development of the Internet, the speed of various types of data has increased in an exploding style. In the prior art, the method for querying data from a storage unit is: according to data which needs to be queried, using a certain language to manually describe the data which needs to be queried, wherein using a certain language to describe the data which needs to be queried is equivalent to writing a query code manually, and a query engine corresponding to the storage unit can run the query code, so as to realize automatical querying of the required data in the storage unit.
However, for different data query needs, different query codes need to be written. Moreover, the storage units of data are diverse, such as a storage unit of a Hadoop type, a storage unit of a Hive type, etc.; if the storage units of data are different, the languages used when processing data needs are also different. Therefore, at present, the method, in which a query code needs to be manually written, can only query data when different languages need to be manually learned and the query code is manually written, causing the data querying efficiency to be low at present.